Principal Applied Scientist- AI

📋 Description

• Lead research and development of large-scale foundation models and agentic AI systems for
• Design novel post-training, model alignment, reinforcement learning, and synthetic data generation
• Develop scalable evaluation frameworks for reasoning, tool use, planning, and autonomous task
• Build production-quality AI systems combining LLMs, multimodal models, retrieval, planning, memory
• Drive innovations in long-context reasoning, workflow generation, and multi-agent orchestration.
• Collaborate with engineering/product teams to transition research into production systems.

🎯 Requirements

• Foundation model training and LLM post-training expertise.
• Reinforcement Learning from Human Feedback (RLHF) and preference optimization.
• Strong programming in Python and deep experience with PyTorch.
• Experience with distributed training/inference and large-scale ML systems.
• Ability to design and run large-scale experiments; data-driven evaluation.
• Excellent communication and cross-team influence skills.

🎁 Benefits

• Flexible work arrangements; hybrid/office/remote options vary by team.
• Diversity and inclusive workplace with equal opportunity for all.
• Reasonable accommodations available on request; privacy and legal disclosures provided.